In various industrial applications, it is frequently necessary to sort workpieces on the basis of their colour signature. This is not an easy task, especially if the workpieces are otherwise identical in size and shape. Traditionally, such sorting has been performed by human operators; however, the results have not always been satisfactory, due to the expense and time involved. In addition, after a short time interval, operator fatigue usually sets in, which leads to sorting errors. These errors are compounded if the differences in colour between the workpiece are small or if the true colour of the workpieces is masked by dirt and grime. For example, a typical operator will have difficulty in distinguishing between a blue workpiece, and a turquoise workpiece, or might mistakenly idenfity a white workpiece that is covered with grime as a beige workpiece.
Various attempts have been made to automate such sorting operations, for example, by correlating the colour of the workpiece with its coefficient of reflection. However, such attempts have not been successful because, as previously mentioned, if the workpieces are soiled, their coefficients of reflection will be diminished, leading to erroneous sorting decisions.